CN115881259A

CN115881259A - Medical record data processing method, device, equipment and storage medium

Info

Publication number: CN115881259A
Application number: CN202211718658.7A
Authority: CN
Inventors: 范春; 徐一涵; 徐安琪; 周炜; 杨吴婕; 马洁; 金灿; 何慧敏; 王涛; 赵大平
Original assignee: Winning Health Technology Group Co Ltd
Current assignee: Winning Health Technology Group Co Ltd
Priority date: 2022-12-29
Filing date: 2022-12-29
Publication date: 2023-03-31

Abstract

The application provides a medical record data processing method, a medical record data processing device, medical record data processing equipment and a storage medium, wherein the method comprises the following steps: acquiring a data item in electronic medical record data of a patient and disease diagnosis information corresponding to the electronic medical record data, determining a medical record label of the patient according to the data item in the electronic medical record data, determining a preset standard data item corresponding to the medical record label of the patient from a preset medical record label rule base of a disease type according to the medical record label of the patient, determining a data item to be completed of the patient according to the data item in the electronic medical record data and a preset standard data item corresponding to the medical record label of the patient, and outputting first reminding information, wherein the first reminding information is used for indicating to complete the data item to be completed in the electronic medical record data. The completeness and quality control of the special medical record data are enhanced by monitoring the completeness, consistency and accuracy of the special medical record data and reminding the to-be-completed medical record items.

Description

Medical record data processing method, device, equipment and storage medium

Technical Field

The present application relates to the field of computer technologies, and in particular, to a method, an apparatus, a device, and a storage medium for processing medical record data.

Background

When a patient-specific database is constructed in clinical research, screening conditions for target data are generally set first, and then data are extracted from a clinical data center or an electronic medical record system according to the screening conditions.

At present, a clinical scientific research execution management platform builds a scientific research integrated platform and a special disease library system on the basis of artificial intelligence through a data Processing system and a scientific research application two board, wherein the data Processing system adopts technologies such as an Extract-Transform-Load (ETL) technology and a Natural Language Processing (NLP) technology to acquire, clean, administer and structurally process clinical data, and the technologies comprise data modeling, warehousing, loading, conversion, desensitization and the like, so that the special disease library suitable for clinical scientific research is formed.

However, the above method mainly combines the technologies of artificial intelligence, data management and the like to retrospectively process the medical record data, so that the medical record data meets the scientific research requirements, but the quality control of the medical record data in the forming process is lacked.

Disclosure of Invention

In view of this, embodiments of the present application provide a method, an apparatus, a device, and a storage medium for processing medical record data, so as to perfect the medical record data and achieve quality control in the process of forming the medical record data.

In a first aspect, an embodiment of the present application provides a medical record data processing method, including:

acquiring data items in electronic medical record data of a patient and disease diagnosis information corresponding to the electronic medical record data, wherein the disease diagnosis information is used for indicating a disease type of the patient;

determining a medical record label of the patient according to a data item in the electronic medical record data, wherein the medical record label is used for indicating a medical service item aiming at the patient under the disease type;

according to the medical record label of the patient, determining a preset standard data item corresponding to the medical record label of the patient from a preset medical record label rule base of the disease type, wherein the medical record label rule base comprises: a plurality of medical record labels aiming at the disease type and preset standard data items corresponding to the medical record labels;

determining a data item to be completed of the patient according to a data item in the electronic medical record data and a preset standard data item corresponding to the medical record label of the patient;

and outputting first reminding information, wherein the first reminding information is used for indicating to perfect the data item to be perfected in the electronic medical record data.

In an optional embodiment, the determining, according to a data item in the electronic medical record data and a preset standard data item corresponding to the medical record label of the patient, a data item to be completed of the patient includes:

updating the completion state of the preset standard data item in the medical record label completion table of the patient aiming at the disease type according to the data item in the electronic medical record data and the preset standard data item corresponding to the medical record label of the patient;

and determining the data item to be completed of the object to be treated according to the completion state of the preset standard data item in the updated medical record label completion table.

In an optional implementation manner, the updating, according to a data item in the electronic medical record data and a preset standard data item corresponding to a medical record label of the patient, a completion state of the preset standard data item in a medical record label completion table of the patient for the disease type includes:

acquiring information of clinical path diagnosis and treatment nodes of the diagnosis object;

updating the completion state of the preset standard data item under the clinical path diagnosis and treatment node in the medical record label completion table according to the data item in the electronic medical record data and the preset standard data item corresponding to the medical record label of the patient under the clinical path diagnosis and treatment node;

the determining, according to the completion state of the preset standard data item in the updated medical record label completion table, a data item to be completed of the patient includes:

and determining the data item to be completed of the object to be diagnosed under the clinical path diagnosis and treatment node according to the completion state of the preset standard data item under the clinical path diagnosis and treatment node in the updated medical record label completion table.

In an optional embodiment, after the outputting the first reminding information, the method further includes:

determining the data capacity of first description information according to the first description information of the data items in the electronic medical record data after completion;

according to the medical record label of the patient, determining the preset standard data capacity of the medical record label of the patient from a medical record data capacity table of the patient post, wherein the medical record data capacity table of the patient post comprises: a plurality of medical record labels for the disease type and preset standard data capacities of the plurality of medical record labels;

and if the capacity difference between the data capacity of the first description information and the preset data capacity of the medical record label of the patient exceeds the preset capacity difference, outputting second reminding information, wherein the second reminding information is used for indicating to perfect the first description information of the data item in the electronic medical record data.

In an optional embodiment, before determining the preset standard data capacity of the medical record label of the patient from the medical record data capacity table of the patient post according to the medical record label of the patient, the method further includes:

acquiring second description information of data items in a plurality of benchmarking medical record data tables corresponding to medical record labels under the disease types;

calculating the data capacity of the second description information of the data items in the plurality of benchmarking medical record data tables;

calculating the preset standard data capacity corresponding to each medical record label according to the data capacity of the second description information;

and generating the medical record data capacity table of the disease category benchmarking according to the preset standard data capacity corresponding to the medical record labels and the medical record labels.

In an optional embodiment, the calculating, according to the data capacity of the second description information, a preset standard data capacity corresponding to each medical record label includes:

and determining the average value of the data capacity of the second description information of the data items in the plurality of benchmarking medical record data tables as the preset standard data capacity corresponding to each medical record label.

In an optional implementation manner, before the obtaining the second description information of the data items in the multiple benchmarked medical record data tables corresponding to the medical record labels under the disease type, the method further includes:

and according to a preset screening condition, determining the medical record data with a data structure meeting the preset screening condition from the plurality of historical medical record data of each medical record label as the plurality of benchmarking medical record data.

In a second aspect, an embodiment of the present application further provides a medical record data processing apparatus, including:

the system comprises an acquisition module, a processing module and a display module, wherein the acquisition module is used for acquiring data items in electronic medical record data of a patient and disease diagnosis information corresponding to the electronic medical record data, and the disease diagnosis information is used for indicating the disease type of the patient;

a determining module, configured to determine, according to a data item in the electronic medical record data, a medical record label of the medical treatment subject, where the medical record label is used to indicate a medical service item for the medical treatment subject;

the determining module is further configured to determine, according to the medical record label of the patient, a preset standard data item corresponding to the medical record label of the patient from a preset medical record label rule base of the disease type, where the preset medical record label rule base includes: a plurality of medical record labels aiming at the disease type and preset standard data items corresponding to the medical record labels;

the determining module is further configured to determine a to-be-completed data item of the patient according to a data item in the electronic medical record data and a preset standard data item corresponding to the medical record label of the patient;

and the output module is used for outputting first reminding information, and the first reminding information is used for indicating the perfection of the data item to be perfected in the electronic medical record data.

In an optional embodiment, the determining module is specifically configured to:

In an optional implementation manner, the determining module is specifically configured to:

acquiring information of a clinical path diagnosis and treatment node of the patient;

In an optional embodiment, the determining module is further configured to:

the output module is further configured to output second prompting information if a capacity difference between the data capacity of the first describing information and a preset data capacity of a medical record label of the patient exceeds a preset capacity difference, where the second prompting information is used to indicate to improve the first describing information of the data item in the electronic medical record data.

In an optional implementation manner, the obtaining module is further configured to:

the device further comprises:

the calculation module is used for calculating the data capacity of the second description information of the data items in the plurality of benchmarking medical record data tables;

the calculation module is further configured to calculate a preset standard data capacity corresponding to each medical record label according to the data capacity of the second description information;

and the generating module is used for generating the medical record data capacity table of the disease category benchmarks according to the preset standard data capacity corresponding to the medical record labels and the medical record labels.

In an optional implementation manner, the calculation module is specifically configured to:

In an optional embodiment, the determining module is further configured to:

In a third aspect, an embodiment of the present application further provides an electronic device, including: the medical record data processing system comprises a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, when the electronic device runs, the processor is communicated with the memory through the bus, and the processor executes the machine-readable instructions to execute the medical record data processing method of any one of the first aspect.

In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program executes the medical record data processing method according to any one of the first aspects.

The application provides a medical record data processing method, a medical record data processing device, medical record data processing equipment and a storage medium, wherein the method comprises the following steps: acquiring a data item in electronic medical record data of a patient and disease diagnosis information corresponding to the electronic medical record data, determining a medical record label of the patient according to the data item in the electronic medical record data, and determining a preset standard data item corresponding to the medical record label of the patient from a preset medical record label rule base of disease types according to the medical record label of the patient, wherein the medical record label rule base comprises: and aiming at a plurality of medical record labels of disease types and preset standard data items corresponding to the medical record labels, determining a data item to be perfected of the patient according to the data item in the electronic medical record data and the preset standard data item corresponding to the medical record label of the patient, and outputting first reminding information, wherein the first reminding information is used for indicating to perfect the data item to be perfected in the electronic medical record data. The completeness and quality control of the special medical record data are enhanced by monitoring the completeness, consistency and accuracy of the special medical record data and reminding the to-be-completed medical record items.

In order to make the aforementioned objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.

Drawings

To more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.

Fig. 1 is a system architecture diagram of a medical record data processing method according to an embodiment of the present application;

fig. 2 is a first flowchart illustrating a medical record data processing method according to an embodiment of the present application;

fig. 3 is a schematic flowchart of a medical record data processing method according to an embodiment of the present application;

fig. 4 is a schematic flowchart of a medical record data processing method according to an embodiment of the present application;

fig. 5 is a fourth schematic flowchart of a medical record data processing method according to an embodiment of the present application;

fig. 6 is a schematic structural diagram of a medical record data processing apparatus according to an embodiment of the present application;

fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.

How to construct a high-quality database of the special disease species which accords with the scientific research dimension is an important work for clinical scientific research or supporting artificial intelligent machine learning. When a patient-specific database is constructed in clinical research, screening conditions for target data are generally set first, and then data are extracted from a clinical data center or an electronic medical record system according to the screening conditions. However, the method lacks discrimination and control on the integrity, consistency, accuracy and information content saturation of the data of the selected target object, so that the selected target object cannot ensure the data quality, cannot provide complete, accurate and detailed data support for scientific research, and influences the scientific research result.

In the existing research, a clinical scientific research execution management platform is constructed by a data processing system and a scientific research application two boards based on artificial intelligence, the data processing system is used for collecting, cleaning, treating and structurally processing clinical data by using the technologies of ETL, NLP and the like, and the special disease library suitable for clinical scientific research is formed by data modeling, warehousing, loading, conversion, desensitization and the like. At present, some hospitals build a whole-hospital-level scientific research integrated platform based on Artificial Intelligence, and based on advanced natural language processing, knowledge charts and other Artificial Intelligence (AI) engines, massive structured and unstructured data in the original clinical business system of the hospital are integrated and treated, so that the structured, standardized and normalized processing of various clinical data is realized.

The method mainly combines the technologies of artificial intelligence, data management and the like to retrospectively process the medical record data so as to enable the medical record data to meet the scientific research requirements, but the quality control of the medical record data in the formation process is lacked, and particularly, a real-time monitoring and improving mechanism is lacked in the aspects of data integrity, consistency, accuracy and information quantity saturation, so that the optimal time window for perfecting the medical record data is missed, and the related data quality problem cannot be solved in the subsequent data management.

Based on the problems, the medical record data processing method is provided, aiming at the electronic medical record generation process of the special disease type, the data quality control is enhanced, in the electronic medical record generation process of the whole-course treatment of a treatment object, the medical record is compared with a rule base corresponding to the disease type through a medical record label as a guide, medical workers are reminded of strengthening the work of the medical record data in the aspects of completeness, consistency, accuracy and information content saturation, the data quality of the special disease type is improved, the medical record data meeting the optimized conditions is extracted, and high-quality sample data is provided for scientific research or artificial intelligent machine learning.

The medical record data processing method provided by the application is described below with reference to several specific embodiments.

Fig. 1 is a system architecture diagram of a medical record data processing method according to an embodiment of the present application, and as shown in fig. 1, the system architecture includes: the medical record management system comprises a collection and matching module, a storage module, a monitoring and reminding module, a medical record data extraction module and a medical record data maintenance module of a disease species benchmarking.

The acquisition and matching module is used for extracting a basic information table of a patient in the table 1 and a medical record label completion table in the table 5; the storage module is used for storing a basic information table of a diagnosis object in a table 1, a corresponding rule table of an electronic medical record data table in a table 2 and medical record labels, a preset medical record label rule table in a table 3, a clinical path diagnosis and treatment node rule table in a table 4, a medical record label completion table in a table 5, a medical record data capacity table in a medical record pole of a disease type in a table 6, medical record data in a pole of a table 7 and an extraction condition table of medical record data in a pole of a table 8; the monitoring and reminding module is used for providing data monitoring and reminding of the special medical record for medical staff aiming at different diagnosis and treatment nodes in clinical path stages such as admission treatment, discharge follow-up visit, discharge rehabilitation, discharge and re-examination and the like in the whole process of seeing a doctor of a patient, and comprises two points: 1. monitoring and reminding the integrity, consistency and accuracy of medical record data of the patient; 2. monitoring and reminding medical record data saturation of the patient; the medical record data extraction module is used for setting extraction conditions of the medical record data of the special diseases, importing the medical record data of the special diseases meeting the conditions into a large clinical data center and providing data support for clinical diagnosis and treatment, scientific research analysis or electronic medical record file management; the disease species benchmarking case history data maintenance module is used for regularly maintaining the disease species benchmarking case history data.

Fig. 2 is a first schematic flow chart of a medical record data processing method according to an embodiment of the present application, where an execution main body of the embodiment may be an electronic device, such as a terminal and a server.

As shown in fig. 2, the method may include:

s101, acquiring data items in the electronic medical record data of the patient and disease diagnosis information corresponding to the electronic medical record data.

In an actual application scenario, medical staff can carry out treatment for a patient in a disease diagnosis and clinical path stage, issue and execute various medical orders, update electronic medical record data of the patient, electronic equipment can be provided with electronic medical record data monitoring software, the medical staff can submit the electronic medical record data of the patient through the software, and disease diagnosis information corresponding to the electronic medical record data, the disease diagnosis information is used for indicating a disease type of the patient, wherein the electronic medical record data comprises a data item, and the data item is a relevant treatment item for the patient, including but not limited to blood type, past medical history, allergy history and the like of the patient.

Wherein, electronic medical record data can be electronic medical record data form, and electronic medical record data form comprises electronic medical record data sub-form, and electronic medical record data sub-form includes the data item, and the data item in the electronic medical record data is the data item in the electronic medical record data sub-form that corresponds, and electronic medical record data form can include for example: medical record summaries, outpatient (emergency) medical records, outpatient (emergency) prescriptions, and the like, wherein the electronic medical record data sub-sheets of the medical record summaries can include, for example: the medical treatment system comprises basic information of a patient, basic health information, a summary of health events and medical expense records, wherein data items in the basic information of the patient comprise: identity (ID), name, sex, date of birth, etc. of the patient.

It should be understood that, during the treatment process, the subject may collect the basic information of the subject, and referring to table 1, table 1 is the basic information table of the subject.

TABLE 1

Referring to table 1, after the hospitalization subject is admitted, the stage of the clinical path of the hospitalization subject, including the stages of admission, preoperative preparation in treatment period, operation, postoperative recovery in treatment period, discharge, etc., and treatment nodes and items in each stage, may be determined and recorded, and the disease diagnosis information includes the admission disease diagnosis code and the admission disease diagnosis name in table 1.

The clinical pathway ID and the clinical pathway name are treatment pathways (the country has a clinical pathway list corresponding to treatment of a disease type) for a certain disease type code (such as ICD-10/11), the clinical pathway includes multiple stages from admission to discharge, and the clinical pathway diagnosis and treatment node is a diagnosis and treatment node subdivided in each stage.

And S102, determining a medical record label of the patient according to the data item in the electronic medical record data.

Different data items correspond to different medical record labels, the data items and the medical record labels can have corresponding relations, the medical record labels of the patients can be determined according to the data items in the electronic medical record data, the medical record labels are used for indicating medical service items aiming at the patients under the disease types, namely the medical service items which should be developed by the patients under the disease types, for example, the data items are blood types, previous medical histories, operation histories and allergy histories, the medical record labels can be the previous medical histories, the data items are symptoms and physical examinations, and the medical record labels are symptoms and physical examinations respectively.

In some embodiments, different medical record labels may correspond to the same data item, so to improve accuracy of the medical record labels, the medical record label of the patient may be determined according to the electronic medical record data sub-form corresponding to the electronic medical record data form and the data item in the electronic medical record data sub-form, that is, one or more medical record labels of the patient are determined by combining the electronic medical record data sub-form and the data item.

It should be noted that the data items in the electronic medical record data sub-form may be core data items in the electronic medical record data sub-form, refer to table 2, and table 2 is a rule table corresponding to the electronic medical record data form and the medical record labels, where table 2 includes the serial number of the electronic medical record data form, the name of the electronic medical record data sub-form, the core data items in the electronic medical record data sub-form, and the medical record labels corresponding to the electronic medical record data sub-form are medical record labels of the subject of diagnosis, and the core data items in the electronic medical record data sub-form refer to "electronic medical record basic data set" released in 10/1/year in the country, and are not listed in a list, so that "a little is used".

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TABLE 2

In table 2, the "electronic medical record data form numbers" are T1 to T17; the name of the electronic medical record data form and the name of the electronic medical record data sub-form are consistent with the national standard of electronic medical record basic data set released and implemented in 1/10/2014, and cover the electronic medical record data full set; the 'electronic medical record data sub-form core data item' is the core data of the electronic medical record data sub-form, and comprises codes, keywords, structured data, texts and other data types; the "medical record label corresponding to the electronic medical record data sub-form" is one or more medical record labels corresponding to the electronic medical record data sub-form.

That is, when the electronic medical record data form of the medical treatment object is changed or submitted, the core data items of the medical record labels in the lookup table 2 are matched according to the data items in the electronic medical record data sub-form, so as to determine the medical record label of the medical treatment object according to the core data items in the electronic medical record data sub-form.

S103, according to the medical record label of the patient, determining a preset standard data item corresponding to the medical record label of the patient from a preset medical record label rule base of the disease type.

The medical record label rule base comprises the following components: and a plurality of medical record labels aiming at the disease type and a plurality of preset standard data items corresponding to the medical record labels.

According to the medical record label of the patient, querying a preset medical record label rule base of the disease type to determine a preset standard data item corresponding to the medical record label of the patient from the preset medical record label rule base, where the preset standard data item may be a data item that is recorded by a plurality of medical record labels under the disease type.

Referring to table 3, table 3 is a preset medical record label rule base table, where a diagnosis code of a disease type is used to indicate the disease type, the disease type may be generated by coding according to international Classification of diseases-10 (ICD-10) or ICD-11, and a clinical path diagnosis node number where a medical record label is located is used to indicate a position of a clinical path diagnosis node where the medical record label is located.

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TABLE 3

As an example, table 3-1 is a medical record label rule base for a specific disease, primary bronchopulmonary carcinoma, and the disease diagnosis codes are: ICD-10: C34/D02.2, non-small cell lung cancer, volar lung resection/lobar resection/total lung resection/thoracoscopy.

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TABLE 3-1

As can be seen from tables 3 and 3-1, the preset standard data items may include, for example: the medical record label sub-items, the position of the corresponding part of the medical record label and the characteristic value in the medical record label.

The medical record label is a medical service item of relevant inspection, examination, treatment, nursing and the like which should be carried out on a certain disease under a corresponding clinical path, the medical record label (sub-item/part) is a subdivision item of the medical record label, for example, the medical record label is 'infectious disease screening', can also be subdivided into screening of hepatitis B, hepatitis C, AIDS, syphilis and the like, the medical record label is 'X-ray radiation', and can also be subdivided into examination of the head, the chest, the abdomen and the like; the medical record label (position of the part) can be understood as that if the content of the medical record label (sub-item/part) refers to a part of the body, the position of the part should be defined, for example, if the part is a chest, the medical record label should be subdivided into a full chest, a left chest, a right chest and the like.

Whether the medical record label is necessary (necessary, one-out-of-many, optional) can be understood as whether the medical record label is an essential item or not for the disease category, and the 'necessary' is the core content of the medical record of the disease category, so that the omission is not allowed, namely, the comparison is carried out according to the preset standard data item of the medical record label to determine the data item to be perfected; the 'one more selected' is that the medical record label of the disease is similar to other medical record labels in the aspects of meaning, method or effect, and the like, for example: the examination of the abdomen, ultrasound or Computer Tomography (CT), can be selected alternatively as long as one item is satisfied without missing, that is, the comparison can be performed according to the preset standard data items of other medical record labels or the preset standard data items of the medical record labels; "optional" is other auxiliary content of the patient medical record, and can be empty.

The characteristic value (if any) in the medical record label can be understood as a characteristic value, a special index or content which marks the disease or is different from other disease types, such as: cough, sputum, hemoptysis, dyspnea, etc., which are symptoms characteristic of certain diseases and distinguished from other diseases, and if any, deletion is not allowed.

Medical record labels are classified into categories of medical record labels such as clinical presentation, examination, imaging examination, pathology examination, other examination, genetic testing, medication, surgery, anesthesia, blood transfusion, radiation therapy, chemotherapy, care, and the like.

And S104, determining a data item to be completed of the patient according to the data item in the electronic medical record data and a preset standard data item corresponding to the medical record label of the patient.

And comparing the contents of the data items in the electronic medical record data with preset standard data items corresponding to medical record labels of the patients, and determining the data items to be perfected of the patients, wherein the data items to be perfected are data items which do not exist in the electronic medical record, but belong to the preset standard data items in contents.

That is to say, according to the disease type of the patient, the medical record label rule base corresponding to the disease type is queried, and the data items in the electronic medical record data and the preset standard data items corresponding to the medical record labels of the patient in the medical record label database are subjected to content association matching, so that the data items which do not exist in the electronic medical record data of the patient are determined as the data items to be improved.

And S105, outputting the first reminding information.

And outputting the first reminding information to indicate to perfect the data item to be perfected in the electronic medical record data, so that medical staff can perfect the data item to be perfected in the electronic medical record data of the object to be diagnosed in time, for example, the data item to be perfected is the position of the corresponding part of the medical record label, and if the content indicated by the medical record label is the chest, the position of the chest of the object to be diagnosed needs to be supplemented and perfected in the electronic medical record data.

In the medical record data processing method of the embodiment, in the whole process of seeing a doctor of a doctor object, the completeness, consistency and accuracy of medical record data of a special disease are monitored by combining the writing process of a clinical electronic medical record, the data to be completed is reminded, so that prompt is timely performed to complete the electronic medical record data, and the completeness and quality control of the medical record data of the special disease are enhanced.

Fig. 3 is a second flowchart of the medical record data processing method according to the embodiment of the present application, and as shown in fig. 3, determining a to-be-completed data item of a patient according to a data item in electronic medical record data and a preset standard data item corresponding to a medical record label of the patient includes:

s201, updating the completion state of the preset standard data item in the medical record label completion table of the patient aiming at the disease type according to the data item in the electronic medical record data and the preset standard data item corresponding to the medical record label of the patient.

S202, determining a data item to be completed of the object to be treated according to the completion state of the preset standard data item in the updated medical record label completion table.

And performing correlation matching on the contents of the data items in the electronic medical record data and the preset standard data items corresponding to the medical record labels of the patients to determine the completion condition of the preset standard data items, and updating the completion state of the preset standard data items in the medical record label completion table according to the completion condition of the preset standard data items.

It should be noted that the completion status of the preset standard data item is not completed by default, and during the hospitalization treatment, the medical staff records the completion status of the preset standard data item by filling in the electronic medical record data, that is, updates the completion status.

And determining the data item with the completion state of unfinished as the data item to be perfected of the diagnosis object according to the completion state of the preset standard data item in the updated medical record label completion table, wherein the data item to be perfected is the data item which is not recorded in the electronic medical record data, and the data item with the completion state of finished is the data item which is recorded in the electronic medical record data.

In a possible implementation manner of step S201, updating a completion status of a preset standard data item in a medical record label completion table of a medical record label of a patient for a disease type according to a data item in the electronic medical record data and a preset standard data item corresponding to a medical record label of the patient includes:

acquiring information of a clinical path diagnosis and treatment node of a patient; and updating the completion state of the preset standard data item under the clinical path diagnosis and treatment node in the medical record label completion table according to the data item in the electronic medical record data and the preset standard data item corresponding to the medical record label of the patient under the clinical path diagnosis and treatment node.

Accordingly, in a possible implementation manner of the step S202, determining the data item to be completed of the medical record subject according to the completion status of the preset standard data item in the updated medical record label completion table includes:

and determining a data item to be completed of the object to be diagnosed under the clinical path diagnosis and treatment node according to the completion state of the preset standard data item under the clinical path diagnosis and treatment node in the updated medical record label completion table.

The method comprises the steps of obtaining electronic medical record data of clinical path diagnosis and treatment nodes of a diagnosis object, obtaining information of the clinical path diagnosis and treatment nodes of the diagnosis object according to the electronic medical record data and preset standard data items corresponding to medical record labels of the diagnosis object under the clinical path diagnosis and treatment nodes, performing correlation matching on contents of the electronic medical record data and the preset standard data items corresponding to the medical record labels of the diagnosis object under the clinical path diagnosis and treatment nodes, updating the completion state of the preset standard data items under the clinical path diagnosis and treatment nodes in a medical record label completion table according to the completion state of the preset standard data items under the clinical path diagnosis and treatment nodes, and determining to-be-completed data items of the diagnosis and treatment object under the clinical path nodes according to the completion state of the preset standard data items under the clinical path diagnosis and treatment nodes in the updated medical record label completion table and the preset standard data items under the clinical path nodes.

That is to say, when the data items in the electronic medical record data and the preset standard data items are associated and matched in content, the clinical path diagnosis and treatment node of the diagnosis target is taken as a consideration factor to determine the preset standard data items under the clinical path diagnosis and treatment node, and the data items in the electronic medical record data and the preset standard data items under the clinical path diagnosis and treatment node are associated and matched in content.

It should be noted that different diagnosis nodes exist in different stages of the clinical pathway, for example, if the clinical pathway stage is admission, the diagnosis nodes include: A1-A5 respectively represent inquiry of medical history, physical examination, preliminary evaluation of disease condition, first ward round, decision of diagnosis and treatment scheme, medical record of hospitalization and first course of disease recording.

Referring to table 4, table 4 is a clinical path diagnosis and treatment node rule base table, which may be established based on a conventional diagnosis and treatment process in clinical path management, and table 4 lists, as an example, only stages and conventional diagnosis and treatment nodes included in a clinical path, and supports a medical worker to maintain the stages and the diagnosis and treatment nodes of the clinical path according to disease types, including addition, deletion, modification, query, storage, and the like of the stages and the diagnosis and treatment nodes, where a disease type code is generated by performing ICD-10 or ICD-11 coding on a disease type.

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TABLE 4

The whole process can be understood as that diagnosis and treatment nodes and items can occur in any diagnosis and treatment stage of hospitalization of the object to be diagnosed for many times, and can be selected as that the item is not necessarily executed in the stage; the surgical species/case applicable can be understood as: the project is only applicable to surgical diseases or cases; non-surgical species/case indications may be understood as: this project is applicable only to non-surgical disease species or cases.

Referring to table 5, table 5 is a medical record label completion table, where the clinical path diagnosis node number where the medical record label is located is consistent with the clinical path diagnosis node number where the medical record label in tables 3 and 3-1 is located, and it can be understood that the corresponding medical record label should be completed in the execution process of the clinical path diagnosis node.

The number of the clinical path diagnosis and treatment node where the medical record label is completed is the number of the clinical path diagnosis and treatment node where the object to be diagnosed is located when the medical record label is actually completed, and the comparison between the target and the actual completion condition is formed.

TABLE 5

See table 3 and table 5 above for comparative display, and associate the medical record label in table 3 with the medical record label in table 5, and can perform comparative display with the preset medical record label rule base of table 3 to show the data completion condition of the object to be diagnosed, and perform comparative analysis with the medical record label as a guide, where the medical record label in table 3, the medical record label in table 5, the completion state of the medical record label, the clinical path diagnosis node number where the medical record label is completed, and the clinical path diagnosis node number where the medical record label is located.

It should be noted that it is also necessary to determine whether an incomplete state exists in table 5 marked as "necessary" or "one-out-of-multiple" in table 3, and in addition, to highlight a label of a medical record in table 5 that is compared abnormally, so as to remind medical staff to complete medical record information in time.

Fig. 4 is a third schematic flow chart of the medical record data processing method provided in the embodiment of the present application, and as shown in fig. 4, after the first reminding information is output, the method may further include:

s301, determining the data capacity of the first description information according to the first description information of the data items in the electronic medical record data after completion.

The first description information is description information of a data item in the electronic medical record data after completion, and description information of the data item for a patient set for a user, for example, if the data item is a past medical history, the first description information of the data item may be "hypertension and hyperglycemia in the past".

The data capacity of the first description information may be the number of bytes of the first description information in bytes (byte).

S302, according to the medical record label of the patient, determining the preset standard data capacity of the medical record label of the patient from the medical record data capacity table of the patient post.

According to the medical record label of the object to be treated, in the 6 disease type benchmarking medical record data capacity tables of the query table, the preset standard data capacity of the medical record label of the object to be treated is determined, wherein the 6 disease type benchmarking medical record data capacity tables comprise: a plurality of medical record labels for the disease type and a plurality of preset standard data capacities of the medical record labels.

And S303, if the capacity difference between the data capacity of the first description information and the preset standard data capacity of the medical record label of the patient exceeds the preset capacity difference, outputting second reminding information.

And calculating that the capacity difference between the data capacity of the first description information and the preset data capacity of the medical record label of the patient exceeds the preset capacity difference, and outputting second reminding information to indicate to perfect the first description information of the data item in the electronic medical record data under the condition that the capacity difference exceeds the preset capacity difference, so that the medical staff can perfect the first description information of the data item in the electronic medical record data of the patient in time.

In the medical record data processing method of the embodiment, in the whole process of seeing a doctor of a patient, the data information saturation of the special medical record data is monitored by combining the writing process of the clinical electronic medical record, and when the capacity difference between the data capacity and the preset standard data capacity exceeds the preset capacity difference, the special medical record data is reminded to prompt the electronic medical record data to be improved in time, so that the completeness and the quality control of the special medical record data are enhanced.

Fig. 5 is a flowchart of a fourth medical record data processing method according to an embodiment of the present application, and as shown in fig. 5, before determining a preset standard data capacity of a medical record label of a patient from a medical record data capacity table of a patient post according to the medical record label of the patient, the method may further include:

s401, second description information of data items in a plurality of benchmarking medical record data tables corresponding to medical record labels under disease types is obtained.

S402, calculating the data capacity of the second description information of the data items in the plurality of benchmarking medical record data tables.

And S403, calculating the preset standard data capacity corresponding to each medical record label according to the data capacity of the second description information.

S404, generating a medical record data capacity table of the disease category benchmarking according to the preset standard data capacity corresponding to the medical record labels and the medical record labels.

And aiming at each medical record label under the disease type, acquiring second description information of the data items in the plurality of benchmarking medical record data tables corresponding to each medical record label, calculating the data capacity of the second description information of the data items in the plurality of benchmarking medical record data tables, and then calculating the preset standard data capacity corresponding to each medical record label according to the data capacity of the second description information of the data items in the plurality of benchmarking medical record data tables.

The preset standard data capacity corresponding to each medical record label may be an average value of the data capacities of the second description information of the data items in the plurality of benchmarking medical record data tables, or may be a weighted sum of the data capacities of the second description information of the data items in the plurality of benchmarking medical record data tables, which is not limited in this embodiment.

In a possible implementation manner of the step S402, determining the preset standard data capacity of each medical record label according to the second description information of the data item in the plurality of benchmarking medical record data tables includes:

The average value of the data capacity of the second description information of the data items in the plurality of benchmarking medical record data tables is calculated, and then the average value is determined to be the preset standard data capacity of each medical record label.

It should be noted that the plurality of benchmarking medical record data is an N-group data set (N can be determined according to actual conditions, such as 20 groups, 50 groups, and the like, where N can be considered as N historical medical subjects corresponding to the disease category, and one historical medical subject corresponds to one group of special medical record data.

Calculating the data capacity mean value of each medical record label of the N groups of sample data, wherein the calculation method of the data capacity mean value of each medical record label comprises the following steps: describing the number of bytes of the description information of the core data item in the table 2 to obtain Ci (i is 1 to N), and obtaining the description information by the aid of the Ci

and/N obtaining the data capacity mean value of each medical record label. Refer to table 6. Table 6 is a medical record data volume table of the disease species benchmarks.

TABLE 6

In the case history data processing method of the embodiment, different diagnosis and treatment nodes of admission treatment, discharge follow-up visit, discharge rehabilitation and discharge double-examination can be selected in the whole process of the patient, a comparison mechanism with the label rule base of the special medical record and the data capacity of the medical record of the patient type benchmarking is established, so that medical workers can refer to and know the quality and progress of the current medical record data record, the completion degree and the data quality of the patient record under different diagnosis and treatment nodes are ensured, and the high-quality requirements of the special electronic medical record on the data in clinical auxiliary decision, scientific research analysis and medical record file management are generally improved.

Before the step S401 obtains the second description information of the data items in the multiple benchmarking medical record data tables corresponding to the medical record labels, the method may further include:

and according to the preset screening conditions, determining the medical record data with the data structure meeting the preset screening conditions from the plurality of historical medical record data of each medical record label as a plurality of benchmarking medical record data.

The medical record labels are provided with a plurality of historical medical record data, and according to a preset screening condition, the medical record data of which the data structure meets the preset screening condition are determined to be a plurality of benchmarking medical record data from the plurality of historical medical record data of the medical record labels, wherein the preset screening condition can be that data items in the medical record data are complete, for example, the medical record labels (sub-items/parts), the medical record labels (positions where the parts are located), and characteristic values (if any) in the medical record labels are complete and are consistent with those in table 3.

That is to say, in order to make the extracted benchmarking medical record data meet the requirement of the core data item, before the benchmarking medical record data is screened from the historical medical record data, the medical record labels corresponding to the historical medical record data in the electronic medical record data form of the table 2 and the corresponding rule table of the medical record labels are firstly inquired, then the medical record label rule base table is preset in the table 3 so as to determine the preset standard data items corresponding to the medical record labels, then when the data items in the historical electronic medical record data meet the preset standard data items in the table 3, the historical medical record data is determined to be the benchmarking medical record data, and then the preset standard data capacity corresponding to each medical record label is calculated according to the data capacity of the second description information of the data items in the multiple benchmarking medical record data tables.

Referring to table 7, table 7 is a benchmarking medical record data table, which includes the number of the electronic medical record data sub-form, the name of the electronic medical record data sub-form, and the core data item of the electronic medical record data sub-form.

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TABLE 7

It is worth to be noted that after the system runs for a period of time, the benchmarking medical record data in the table 7 can be maintained and updated regularly, and sample data with higher standards and better quality can be screened out through preset screening conditions to improve the quality of the medical record data of the disease.

In an actual application scene, the medical record data of the special diseases comprises the record of the whole process from hospitalization treatment to discharge follow-up visit, rehabilitation and re-examination and the process has long time span and large change frequency difference of the medical record data (for example, the medical record change time span during hospitalization is short, the medical record change time span is dense and frequent, the medical record change time span during discharge follow-up visit, rehabilitation or re-examination and the frequency is small), so that the medical record data of the special diseases can be conveniently applied and analyzed in the follow-up time, and the electronic medical record data of the special diseases can be extracted by selecting corresponding diagnosis and treatment nodes in the whole process of hospitalization of the hospitalization objects according to the requirements of clinical diagnosis, scientific research analysis, electronic medical record file management and the like, and the data support can be provided for the application of large data such as clinical auxiliary diagnosis, scientific research teaching, file management and the like.

In some embodiments, the conditions for extracting the medical record data of the specific disease can be set, including setting a combination condition for one or more of the conditions according to a disease diagnosis code, sex and age of a patient, a diagnosis node where the patient is located, a medical record label, data capacity of the medical record label, and the like, and importing the medical record data (form) of the specific disease meeting the conditions into a clinical big data center to provide data support for clinical diagnosis, scientific research analysis or electronic medical record file management.

Referring to table 8, table 8 is an extraction condition table of medical record data, which includes condition types and condition settings, and can be specifically set according to actual situations.

TABLE 8

Based on the same inventive concept, the embodiment of the present application further provides a medical record data processing apparatus corresponding to the medical record data processing method, and since the principle of the apparatus in the embodiment of the present application for solving the problem is similar to that of the medical record data processing method in the embodiment of the present application, the implementation of the apparatus can refer to the implementation of the method, and repeated details are not described again.

Fig. 6 is a schematic structural diagram of a medical record data processing apparatus according to an embodiment of the present application, where the apparatus may be integrated in an electronic device. As shown in fig. 6, the apparatus may include:

an obtaining module 501, configured to obtain a data item in electronic medical record data of a patient and disease diagnosis information corresponding to the electronic medical record data, where the disease diagnosis information is used to indicate a disease type of the patient;

a determining module 502, configured to determine, according to a data item in the electronic medical record data, a medical record label of the patient, where the medical record label is used to indicate a medical service item for the patient;

the determining module 502 is further configured to determine, according to the medical record label of the patient, a preset standard data item corresponding to the medical record label of the patient from a preset medical record label rule base of the disease type, where the preset medical record label rule base includes: a plurality of medical record labels aiming at disease types and preset standard data items corresponding to the medical record labels;

the determining module 502 is further configured to determine a to-be-completed data item of the medical treatment subject according to the data item in the electronic medical record data and a preset standard data item corresponding to the medical record label of the medical treatment subject;

the output module 503 is configured to output first prompting information, where the first prompting information is used to instruct to complete a data item to be completed in the electronic medical record data.

In an optional implementation, the determining module 502 is specifically configured to:

and determining the data item to be completed of the object to be diagnosed according to the completion state of the preset standard data item in the updated medical record label completion table.

In an optional embodiment, the determining module 502 is specifically configured to:

acquiring information of a clinical path diagnosis and treatment node of a patient;

updating the completion state of the preset standard data item under the clinical path diagnosis and treatment node in a medical record label completion table according to the data item in the electronic medical record data and the preset standard data item corresponding to the medical record label of the patient under the clinical path diagnosis and treatment node;

and determining the data items to be completed of the medical treatment objects under the clinical path diagnosis and treatment nodes according to the completion state of the preset standard data items under the clinical path diagnosis and treatment nodes in the updated medical record label completion table.

In an optional implementation, the determining module 502 is further configured to:

determining the data capacity of the first description information according to the first description information of the data items in the electronic medical record data after the completion;

according to the medical record label of the patient, the preset standard data capacity of the medical record label of the patient is determined from the medical record data capacity table of the patient post, and the medical record data capacity table of the patient post comprises: a plurality of medical record labels for the disease type and a plurality of preset standard data capacities of the medical record labels;

and the output module is further used for outputting second reminding information if the capacity difference between the data capacity of the first description information and the preset standard data capacity of the medical record label of the patient exceeds the preset capacity difference, wherein the second reminding information is used for indicating the perfection of the first description information of the data item in the electronic medical record data.

In an optional embodiment, the obtaining module 501 is further configured to:

the device also includes:

a calculating module 504, configured to calculate data capacities of second description information of data items in the multiple benchmarking medical record data tables;

the calculating module 504 is further configured to calculate a preset standard data capacity corresponding to each medical record label according to the data capacity of the second description information;

the generating module 505 is configured to generate a medical record data capacity table of the medical record benchmarks according to the preset standard data capacity corresponding to the plurality of medical record labels and the plurality of medical record labels.

In an optional implementation, the calculating module 504 is specifically configured to:

In an optional embodiment, the determining module 502 is further configured to:

The description of the processing flow of each module in the device and the interaction flow between the modules may refer to the related description in the above method embodiments, and will not be described in detail here.

Fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application, and as shown in fig. 7, the electronic device may include: the medical record data processing system comprises a processor 601, a memory 602 and a bus 603, wherein the memory 602 stores machine-readable instructions executable by the processor 601, when the electronic device runs, the processor 601 and the memory 602 communicate through the bus 603, and the processor 601 executes the machine-readable instructions to execute the medical record data processing method.

The embodiment of the application also provides a computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the processor executes the medical record data processing method.

In the embodiments of the present application, when being executed by a processor, the computer program may further execute other machine-readable instructions to perform other methods as described in the embodiments, and for the method steps and principles of specific execution, reference is made to the description of the embodiments, and details are not repeated here.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed coupling or direct coupling or communication connection between each other may be through some communication interfaces, indirect coupling or communication connection between devices or units, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments provided in the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus once an item is defined in one figure, it need not be further defined and explained in subsequent figures, and moreover, the terms "first", "second", "third", etc. are used merely to distinguish one description from another and are not to be construed as indicating or implying relative importance.

Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present application, and are used for illustrating the technical solutions of the present application, but not limiting the same, and the scope of the present application is not limited thereto, and although the present application is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope disclosed in the present application; such modifications, changes or substitutions do not depart from the spirit and scope of the present disclosure, which should be construed in light of the above teachings. Are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A medical record data processing method is characterized by comprising the following steps:

2. The method according to claim 1, wherein the determining the data item to be completed of the medical treatment subject according to the data item in the electronic medical record data and the preset standard data item corresponding to the medical record label of the medical treatment subject comprises:

and determining the data item to be completed of the patient according to the completion state of the preset standard data item in the updated medical record label completion table.

3. The method according to claim 2, wherein the updating the completion status of the preset standard data item in the medical record label completion table of the patient for the disease type according to the data item in the electronic medical record data and the preset standard data item corresponding to the medical record label of the patient comprises:

and determining the data item to be completed of the diagnosis object under the clinical path diagnosis and treatment node according to the completion state of the preset standard data item under the clinical path diagnosis and treatment node in the updated medical record label completion table.

4. The method of claim 1, wherein after outputting the first reminder information, the method further comprises:

determining the data capacity of first description information according to the first description information of data items in the electronic medical record data after completion;

5. The method of claim 4, wherein before determining the predetermined standard data capacity of the medical record label of the patient from the patient post medical record data capacity table according to the medical record label of the patient, the method further comprises:

6. The method according to claim 5, wherein the calculating the preset standard data capacity corresponding to each medical record label according to the data capacity of the second description information includes:

7. The method according to claim 5, wherein before the obtaining the second description information of the data items in the benchmarked medical record data tables corresponding to the medical record labels under the disease type, the method further comprises:

8. A medical record data processing apparatus, comprising:

9. An electronic device, comprising: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, the processor and the memory communicate with each other through the bus when the electronic device runs, and the processor executes the machine-readable instructions to execute the medical record data processing method according to any one of claims 1 to 7.

10. A computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium, and when executed by a processor, the computer program performs the medical record data processing method according to any one of claims 1 to 7.